5 Leaders Reveal Bold AI & Security Predictions for 2026: From Meta-Agents to Malwareless Attacks скачать в хорошем качестве

5 Leaders Reveal Bold AI & Security Predictions for 2026: From Meta-Agents to Malwareless Attacks

The technology landscape is evolving at breakneck speed, and 2026 promises to be a pivotal year for AI adoption, cybersecurity threats, and software development practices. We gathered predictions from five industry leaders spanning DevOps, security, and artificial intelligence to understand what's coming next. Strategic AI Collaboration Will Define Winners Emilio Salvador, VP of Strategy and Developer Relations at GitLab, argues that speed of AI adoption won't determine success in 2026. Instead, companies that strategically implement AI across the entire software development lifecycle will emerge as winners. Salvador predicts a shift toward 50/50 human-agent collaboration, where organizations identify optimal integration points rather than rushing to automate everything. More dramatically, Salvador envisions the rise of "meta-agents"—agents managing other agents that function as full team members with email accounts and Slack profiles. These autonomous systems will work proactively, identifying tasks requiring their expertise without explicit assignment, fundamentally changing how development teams operate around the clock. Adversaries Will Weaponize AI at Industrial Scale Matt Mullins, Head Hacker and Offensive SME at Reveal Security, warns that 2026 will see adversaries leveraging AI capabilities more fully. While autonomous hacking systems remain unlikely, sophisticated deepfakes will move beyond prototype phase to industrial-scale deployment. Recent data shows exploitation times have already dropped to one day or less, and AI-powered tools will accelerate this further, allowing single ransomware operators to accomplish what previously required entire teams. Mullins also predicts increased focus on identity security as hybrid environments blur on-premises and cloud boundaries. Perhaps most concerning, he anticipates a rise in malwareless attacks, where adversaries use legitimate remote access tools like TeamViewer—already whitelisted by IT departments—instead of developing custom malware, significantly reducing detection risk. AI Attacks Become Multi-Step and Autonomous Tim Erlin, VP of Product at Wallarm, focuses on how attackers will use AI to execute complex, multi-step attacks without human intervention. Previously, chaining exploits together required humans to make decisions at each stage. Generative AI agents can now reason through next steps autonomously, dramatically expanding attack sophistication. Erlin predicts market consolidation around application security in 2026, as customers recognize that web application protection, API security, and AI security address a single problem: protecting applications regardless of deployment technology. He also expects standardization in AI security to emerge, drawing parallels to past technology cycles. Erlin specifically highlights the A2AS standard from a.org as a community-driven framework likely to gain adoption. Workforce Reskilling and Energy Costs Will Surge Joseph Kim, CEO of Druid AI, predicts massive workforce reskilling as agentic AI proliferates. Drawing from conversations with engineering leaders at major tech companies, Kim notes that AI coding assistants feel like having hundreds of junior developers constantly requesting feedback. Managing these AI capabilities will require new skills across organizations. Kim also warns of impending data center capacity shortages and exploding energy costs driven by AI workload demands. However, he expects this pressure to drive innovation in energy efficiency. Finally, Kim predicts that business applications will experience an uplift in value as chat and agentic interfaces become the primary way users interact with enterprise data, fundamentally transforming how organizations extract insights. The Incident Landscape Is Shifting Dramatically JJ Tang, founder and CEO of Rootly, highlights a critical challenge: AI-generated code is changing the nature of software incidents. With AWS reporting that 75% of production code is now AI-generated, and studies showing 25% productivity gains, developers are shipping more code faster. However, statistical probability suggests more changes mean more potential breakage. Tang warns that developers are becoming less familiar with their own codebases as coding shifts from writing lines to prompting AI. When incidents occur, SREs will find less help from developers who didn't manually write the problematic code. The silver lining? A new class of AISR tools is emerging to automatically investigate root causes and suggest fixes, democratizing incident response beyond traditional development teams. Timestamp: 00:00 Intro 00:23 Emilio Salvador of GitLab: 2026 Predictions 02:32 Matt Mullins of Reveal Security: 2026 Predictions 05:20 Tim Erlin of Wallarm: 2026 Predictions 08:28 Joseph Kim of Druid AI: 2026 Predictions 11:05 JJ Tang of Rootly: 2026 Predictions